Statistics: The Art and Science of Learning from Data (4th Edition) - 4th Edition - by Alan Agresti, Christine A. Franklin, Bernhard Klingenberg - ISBN 9780321997838

Statistics: The Art and Science of Lear...
4th Edition
Alan Agresti, Christine A. Franklin, Bernhard Klingenberg
Publisher: PEARSON
ISBN: 9780321997838

Solutions for Statistics: The Art and Science of Learning from Data (4th Edition)

Browse All Chapters of This Textbook

Chapter 2.6 - Recognizing And Avoiding Misuses Of Graphical SummariesChapter 3 - Association: Contingency, Correlation, And RegressionChapter 3.1 - The Association Between Two Categorical VariablesChapter 3.2 - The Association Between Two Quantitative VariablesChapter 3.3 - Predicting The Outcome Of A VariableChapter 3.4 - Cautions In Analyzing AssociationsChapter 4 - Gathering DataChapter 4.1 - Experimental And Observational StudiesChapter 4.2 - Good And Poor Ways To SampleChapter 4.3 - Good And Poor Ways To ExperimentChapter 4.4 - Other Ways To Conduct Experimental And Nonexperimental StudiesChapter 5 - Probability In Our Daily LivesChapter 5.1 - How Probability Quantifies RandomnessChapter 5.2 - Finding ProbabilitiesChapter 5.3 - Conditional ProbabilityChapter 5.4 - Applying The Probability RulesChapter 6 - Probability DistributionsChapter 6.1 - Summarizing Posible Outcomes And Their ProbabilitiesChapter 6.2 - Probabilities For Bell-shaped DistributionsChapter 6.3 - Probabilities When Each Observation Has Two Possible OutcomesChapter 7 - Sampling DistributionsChapter 7.1 - How Sample Proportions Vary Around The Population ProportionChapter 7.2 - How Sample Proportions Vary Around The Population MeanChapter 8 - Statistical Inference: Confidence IntervalsChapter 8.1 - Point And Interval Estimates Of Population ParametersChapter 8.2 - Constructing A Confidence Interval To Estimate A Population ProportionChapter 8.3 - Constructing A Confidence Interval To Estimate A Population MeanChapter 8.4 - Choosing The Sample Size For A StudyChapter 8.5 - Using Computers To Make New Estimation Methods PossibleChapter 9 - Statistical Inference: Significance Tests About HypothesesChapter 9.1 - Steps For Performing A Significance TestChapter 9.2 - Significance Tests About ProportionsChapter 9.3 - Significance Tests About MeansChapter 9.4 - Decisions And Types Of Errors In Significance TestsChapter 9.5 - Limitations Of Significance TestsChapter 9.6 - The Likelihood Of A Type Ii Error And The Power Of A TestChapter 10 - Comparing Two GroupsChapter 10.1 - Categorical Response: Comparing Two ProportionsChapter 10.2 - Quantitative Response: Comparing Two MeansChapter 10.3 - Other Ways Of Comparing Means, Including A Permutation TestChapter 10.4 - Analyzing Dependent SamplesChapter 10.5 - Adjusting For The Effects Of Other VariablesChapter 11 - Analyzing The Association Between Categorical VariablesChapter 11.1 - Independence And Dependence (association)Chapter 11.2 - Testing Categorical Variables For IndependanceChapter 11.3 - Determining The Strength Of The AssociationChapter 11.4 - Using Residuals To Reveal The Pattern Of AssociationChapter 11.5 - Fisher's Exact And Permutation TestsChapter 12 - Analyzing The Association Between Quantitative Variables: Regression AnalysisChapter 12.1 - Modelling How Two Variables Are RelatedChapter 12.2 - Inference About Model Parameters And The AssociationChapter 12.3 - Describing The Strength Of AssociationChapter 12.4 - How The Data Vary Around The Regression LineChapter 12.5 - Exponential Regression: A Model For NonlinearityChapter 13 - Multile RegressionChapter 13.1 - Using Several Variables To Predict A ResponseChapter 13.2 - Extending The Correlation And R2 For Multiple RegressionChapter 13.3 - Inferences Using Multiple RegressionChapter 13.4 - Checking A Regression Model Using Residual PlotsChapter 13.5 - Regression And Categorical PredictorsChapter 13.6 - Modeling A Categorical ResponseChapter 14 - Comparing Groups: Analysis Of Variance MethodsChapter 14.1 - One-way Anova: Comparing Several MeansChapter 14.2 - Estimating Differences In Groups For A Single FactorChapter 14.3 - Two-way AnovaChapter 15 - Nonparametric StatisticsChapter 15.1 - Compare Two Grouups By RankingChapter 15.2 - Nonparametric Methods For Several Groups And For Matched Pairs

Book Details

Statistics: The Art and Science of Learning from Data, Fourth Edition, takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analyzing data, rather than just memorizing procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.


The authors believe that it's important for students to learn and analyze both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data.


More Editions of This Book

Corresponding editions of this textbook are also available below:

5th Edition
ISBN: 9780136679127
1st Edition
ISBN: 9781118953723
3rd Edition
ISBN: 9780321755940
Statistics: The Art And Science Of Learning From Data Plus Mymathlab Student Access Kit (2nd Edition)
2nd Edition
ISBN: 9780321747181
Statistics, Books a la Carte Edition Plus MyLab Statistics with Pearson eText -- Access Card Package (4th Edition)
4th Edition
ISBN: 9780134435855
Statistics: The Art and Science of Learning From Data, Books a la Carte Edition (4th Edition)
4th Edition
ISBN: 9780133860825
4th Edition
ISBN: 9780134436814
4th Edition
ISBN: 9780135989029
4th Edition
ISBN: 8220102019805

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